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CMU-CS-06-106
Computer Science Department
School of Computer Science, Carnegie Mellon University
CMU-CS-06-106
New Techniques for Private Stream Searching
John Bethencourt, Dawn Song, Brent Waters*
February 2006
CMU-CS-06-106.ps
CMU-CS-06-106.pdf
Keywords: Private stream searching, private information retrieval,
public key program obfuscation, systems of linear equations, Bloom filters,
homomorphic encryption
A system for private stream searching, introduce by Ostrovsky
and Skeith, allows a client to provide an untrusted server with an
encrypted search query.
A system for private stream searching, introduced by Ostrovsky and
Skeith, allows a client to provide an untrusted server with an
encrypted search query. The server uses the query on a stream
of documents and returns the matching documents to the client while
learning nothing about the nature of the query. We present a new
scheme for conducting private keyword search on streaming
data which requires O(m) server to client communication
complexity to return the content of the matching documents,
where m is the size of the documents. The required storage on the
server conducting the search is also O(m). Our technique requires
some metadata to be returned in addition to the documents; for this
we present a scheme with O(m log(t/m)) communication
and storage complexity. In many streaming applications, the number
of matching documents is expected to be a fixed fraction of the
stream length; in this case the new scheme has the optimal
O(m) overall communication and storage complexity with near optimal
constant factors. The previous
best scheme for private stream searching was shown to have O(m log m)
communication and storage complexity. In applications where t/m > m,
we may revert to an alternative method of returning the necessary
metadata which has O(mlogm) communication and storage complexity;
in this case constant factor improvements over the previous scheme
are achieved. Our solution employs a novel construction in which the
user reconstructs the matching files by solving a system
of linear equations. This allows the matching documents to be
stored in a compact buffer rather than relying on redundancies to
avoid collisions in the storage buffer as in previous work.
We also present a unique encrypted Bloom filter construction which
is used to encode the set of matching documents. In this paper we
describe our scheme, prove it secure, analyze its asymptotic
performance, and describe several extensions.
26 pages
*SRI International
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